Digital camera device and methodology for distributed processing and wireless transmission of digital images

ABSTRACT

A digital imaging system is described that provides techniques for reducing the amount of processing power required by a given digital camera device and for reducing the bandwidth required for transmitting image information to a target platform. The system defers and/or distributes the processing between the digital imager (i.e., digital camera itself) and the target platform that the digital imager will ultimately be connected to. In this manner, the system is able to decrease the actual computation that occurs at the digital imager. Instead, the system only performs a partial computation at the digital imager device and completes the computation somewhere else, such as at a target computing device (e.g., desktop computer) where time and size are not an issue (relative to the imager). By deferring resource-intensive computations, the present invention substantially reduces the processor requirements and concomitant battery requirements for digital cameras. Further, by adopting an image strategy optimized for compression (compressed luminosity record), the present invention decreases the bandwidth requirements for transmitting images, thereby facilitating the wireless transmission of digital camera images.

RELATED APPLICATIONS

The present application claims the benefit of priority from and isrelated to the following commonly-owned U.S. provisional application:application Ser. No. 60/138,168, filed Jun. 8, 1999. The disclosure ofthe foregoing application is hereby incorporated by reference in itsentirety, including any appendices or attachments thereof, for allpurposes.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyrightrights whatsoever.

BACKGROUND OF THE INVENTION

The present invention relates to the field of digital cameras anddigital image processing and, more particularly, to designs andtechniques for reducing processing requirements and therefore size ofdigital cameras.

Today, digital imaging, particularly in the form of digital cameras, isa prevalent reality that affords a new way to capture photos using asolid-state image sensor instead of traditional film. A digital camerafunctions by recording incoming light on some sort of sensing mechanismsand then processes that information (basically, throughanalog-to-digital conversion) to create a memory image of the targetpicture. A digital camera's biggest advantage is that it creates imagesdigitally thus making it easy to transfer images between all kinds ofdevices and applications. For instance, one can easily insert digitalimages into word processing documents, send them by e-mail to friends,or post them on a Web site where anyone in the world can see them.Additionally, one can use photo-editing software to manipulate digitalimages to improve or alter them. For example, one can crop them, removered-eye, change colors or contrast, and even add and delete elements.Digital cameras also provide immediate access to one's images, thusavoiding the hassle and delay of film processing. All told, digitalphotography is becoming increasingly popular because of the flexibilityit gives the user when he or she wants to use or distribute an image.

The defining difference between digital cameras and those of the filmvariety is the medium used to record the image. While a conventionalcamera uses film, digital cameras use an array of digital image sensors.When the shutter opens, rather than exposing film, the digital cameracollects light on an image sensor, a solid state electronic device. Theimage sensor contains a grid of tiny photosites that convert lightshining on them to electrical charges. The image sensor may be of thecharged-coupled device (CCD) or complementary metal-oxide semiconductor(CMOS) varieties. Most digital cameras employ charge-coupled device(CCD) image sensors, but newer cameras are using image sensors of thecomplimentary metal-oxide semiconductor (CMOS) variety. Also referred toby the acronym CIS (for CMOS image sensors), this newer type of sensoris less expensive than its CCD counterpart and requires less power.

During camera operation, an image is focused through the camera lens sothat it will fall on the image sensor. Depending on a given image,varying amounts of light hit each photosite, resulting in varyingamounts of electrical charge at the photosites. These charges can thenbe measured and converted into digital information that indicates howmuch light hit each site which, in turn, can be used to recreate theimage. When the exposure is completed, the sensor is much like acheckerboard, with different numbers of checkers (electrons) piled oneach square (photosite). When the image is read off of the sensor, thestored electrons are converted to a series of analog charges which arethen converted to digital values by an Analog-to-Digital (A to D)converter, which indicates how much light hit each site which, in turn,can be used to recreate the image.

Early on during the digital imaging process, the picture information isnot in color as the image sensors basically only capture brightness.They can only record gray-scale information—that is, a series ofincreasingly darker tones ranging from pure white to pure black. Thus,the digital camera must infer certain information about the picture inorder to derive the color of the image. To infer color from this black &white or grayscale image, digital cameras use color filters to separateout the different color components of the light reflected by an object.Popular color filter combinations include, for instance, a red, green,and blue (RGB) filter set and a cyan, magenta, and yellow (CMYK) filterset. Filters can be placed over individual photosites so each cancapture only one of the filtered colors. For an RGB implementation, forexample, one-third of the photo is captured in red light, one-third inblue, and one-third in green. In such an implementation, each pixel onthe image sensor has red, green, and blue filters intermingled acrossthe photosites in patterns designed to yield sharper images and truercolors. The patterns vary from company to company but one of the mostpopular is the Bayer mosaic pattern, which uses a square for four cellsthat include two green on one diagonal, with one red and one blue on theopposite diagonal.

Because of the color filter pattern, only one color luminosity value iscaptured per sensor pixel. To create a full-color image, interpolationis used. This form of interpolation uses the colors of neighboringpixels to calculate the two colors a photosite did not record. Bycombining these two interpolated colors with the color measured by thesite directly, the original color of every pixel is calculated. Thisstep is compute-intensive since comparisons with as many as eightneighboring pixels is required to perform this process properly. It alsoresults in increased data per image so files get larger.

In order to generate an image of quality that is roughly comparable to aconventional photograph, a substantial amount of information must becapture and processed. For example, a low-resolution 640×480 image has307,200 pixels. If each pixel uses 24 bits (3 bytes) for true color, asingle image takes up about a megabyte of storage space. As theresolution increases, so does the image's file size. At a resolution of1024×768, each 24-bit picture takes up 2.5 megabytes. Because of thelarge size of this information, digital cameras usually do not store apicture in its raw digital format but, instead, apply compressiontechnique to the image so that it can be stored in a standard compressedimage format, such as JPEG (Joint Photographic Experts Group).Compressing images allows the user to save more images on the camera's“digital film,” such as flash memory (available in a variety of specificformats) or other facsimile of film. It also allows the user to downloadand display those images more quickly.

During compression, data that is duplicated or which has no value iseliminated or saved in a shorter form, greatly reducing a file's size.When the image is then edited or displayed, the compression process isreversed. In digital photography, two forms of compression are used:lossless and lossy. In lossless compression (also called reversiblecompression), reversing the compression process produces an image havinga quality that matches the original source. Although losslesscompression sounds ideal, it doesn't provide much compression.Generally, compressed files are still a third the size of the originalfile, not small enough to make much difference in most situations. Forthis reason, lossless compression is used mainly where detail isextremely important as in x-rays and satellite imagery. A leadinglossless compression scheme is LZW (Lempel-Ziv-Welch). This is used inGIF and TIFF files and achieves compression ratios of 50 to 90%.

Although it is possible to compress images without losing some quality,it's not practical in many cases. Therefore, all popular digital camerasuse a lossy compression. Although lossy compression does not uncompressimages to the same quality as the original source, the image remainsvisually lossless and appears normal. In many situations, such asposting images on the Web, the image degradation is not obvious. Thetrick is to remove data that isn't obvious to the viewer. For example,if large areas of the sky are the same shade of blue, only the value forone pixel needs to be saved along with the locations of where the otheridentical pixels appear in the image.

The leading lossy compression scheme is JPEG (Joint Photographic ExpertsGroup) used in JFIF files (JPEG File Interchange Format). JPEG is alossy compression algorithm that works by converting the spatial imagerepresentation into a frequency map. A Discrete Cosine Transform (DCT)separates the high- and low-frequency information present in the image.The high frequency information is then selectively discarded, dependingon the quality setting. The greater the compression, the greater thedegree of information loss. The scheme allows the user to select thedegree of compression, with compression ratios between 10:1 and 40:1being common. Because lossy compression affects the image, most camerasallow the user to choose between different levels of compression. Thisallows the user to choose between lower compression and higher imagequality, or greater compression and poorer image quality.

One would think with present-day digital technology and scale, one couldcreate a digital camera that is extremely small and portable,particularly since a digital camera is not constrained by the physicalconstraints of traditional photographic film. This is not the casetoday, however. As it turns out, the whole process of capturing lightand generating a color digital image, such as with a digital camera, isa very compute-intensive process. Further, the resulting images storedat digital cameras today are comparatively large (e.g., image size ofone-half megabyte or more is common), thus making it unattractive todownload images using wireless (e.g., cellular phone) transmission. Theprocess of recording an image on photographic film, in comparison,relies on straightforward chemical reactions, all without the need forcomputing resources. A digital image, however, entails a process ofconverting light into electrical signals, converting those electricalsignals into digital or binary information, arranging that informationinto a visual representation, applying various digital filters and/ortransformations, interpolating color from that representation, and soforth and so on. The process of rendering a meaningful digital pictureis a compute-intensive undertaking, roughly equivalent in processingpower to that required today for a desktop workstation, yet done sowithin the confines of a hand-held portable device.

The upshot of this substantial processing requirement is that,paradoxically, digital cameras today are relatively bulky devices sincethey require relatively large batteries to support their processingneeds. This is easily seen today in camera designs. For instance,digital cameras by Sony employ large custom lithium batteries. Othercamera designs employ four to six AA batteries—a fairly bulkyarrangement. Even with all those batteries, digital cameras today haverelatively short battery lives, such that the digital camera user isrequired to change out batteries at frequent intervals. Perhaps thebiggest drawback of such an approach, however, is the added bulkimparted to the camera itself with such a design. Today, most of theweight of a digital camera is attributable to its batteries. Thus,present-day digital cameras, been constrained by their batteryrequirements, are generally no smaller or portable than theirnon-digital counterparts (e.g., standard 35 mm camera). And the smallestcameras today still remain film-based cameras, not digital ones, due inlarge part to the battery constraints of digital cameras.

Current approaches to reducing camera size have relied on improvementsto the underlying silicon (e.g., microprocessor) technology. Forexample, one approach is that of increased integration, such as usingcustom chip sets that are specialized for digital cameras. Examplesinclude, for instance, products offered by Sierra Imaging of ScottsValley, Calif. and VLSI Vision Ltd. of Edinburgh, Scotland. The basicgoal is to decrease a camera's energy requirements by super-integratingmany of the digital camera's components onto a single chip, therebyrealizing at least some energy savings by eliminating energyrequirements for connecting external components. Another approach is torely on ever-improving silicon technology. Over time, as silicontechnology evolves (e.g., with higher transistor densities),ever-increasing compute power is available for a given energy ratio.Either approach does not address the underlying problem that acompute-intensive process is occurring at the digital camera, however.Moreover, the approaches do not address the problem that large imagesizes pose to wireless transmission. As a result, the improvementafforded by increased integration or improvements in transistor densityprovide incremental improvement to camera size, with little or noimprovement in the area of wireless transmission or downloading ofimages.

Moreover, as silicon technology improves, a competing interest comesinto play. The marketplace is demanding better image quality and betterimage resolution. To the extent that improved silicon technology becomesavailable, that technology by and large is being applied to improvingthe output of digital cameras, not to decreasing their powerrequirements (and thereby their size). The net result is thatimprovements to silicon technology have resulted in better resolutionbut little or no change in camera size.

Another approach is to focus on improving the underlying imagecompression methodology itself, apart from the other aspects of imageprocessing. For instance, one could envision a better compressiontechnique that reduces computational requirements by reducing the amountof image data (e.g., using “lossy” compression methodology)substantially more than is presently done. Unfortunately, efforts todate have resulted in images of relatively poor quality, thus negatingimprovements to resolution afforded by improved silicon technology.Although future improvements will undoubtedly be made, such improvementsare—like those to silicon technology—likely to be incremental.

Given the substantial potential that digital imaging holds, thereremains great interest in finding an approach today for substantiallydecreasing the size of digital cameras and improving the downloading ofimages, particularly in a wireless manner, but doing so in a manner thatdoes not impair image quality. In particular, what is needed is adigital camera that allows users to enjoy the benefits of digitalimaging but without the disadvantages of present-day bulky designs withtheir lengthy image download transmission times. The present inventionfulfills this and other needs.

SUMMARY OF THE INVENTION

A digital imaging system of the present invention implements amethodology for distributed processing and wireless transmission ofdigital images. The digital image system, implemented as a digitalcamera in the currently-preferred embodiment, includes a Sensor, aShutter Actuator, an Image Processor, an Image (DRAM) Memory, a(Central) Processor, a Keypad and Controls, a Program Code Flash Memory,a (System) Memory, a Direct View Display, a Hot Shoe Interface, and a“Digital Film” Flash Memory. These various components communicate withone another using a bus architecture including, for instance, an AddressBus, a Data Bus, and an I/O (Input/Output) Bus.

The basic approach adopted by the present invention is to adopttechniques for reducing the amount of processing power required by agiven digital camera device and for reducing the bandwidth required fortransmitting image information to a target platform. Given that digitalcameras exist in a highly-connected environment (e.g., one in whichdigital cameras usually transfer image information to other computingdevices), there is an opportunity to take advantage of other processingpower that is eventually going to come into contact with the images thatare produced by the digital imaging device (“imager”). Moreparticularly, there is an opportunity to defer and/or distribute theprocessing between the digital imager itself and the target platformthat the digital imager will ultimately be connected to, either directlyor indirectly. The approach of the present invention is, therefore, todecrease the actual computation that occurs at the digital imager:perform a partial computation at the digital imager device and completethe computation somewhere else—somewhere where time and size are not anissue (relative to the imager). By “re-architecting” the digital camerato defer resource-intensive computations, the present invention maysubstantially reduce the processor requirements and concomitant batteryrequirements for digital cameras. Further, the present invention adoptsan image strategy which reduces the bandwidth requirements fortransmitting images, thereby facilitating the wireless transmission ofdigital camera images.

A preferred methodology of the present invention for digital imageprocessing includes the following steps. At the outset, an image iscaptured by a capture process; this may be done in a conventionalmanner. Next, however, the color interpolation or transformation processof conventional digital image processing is entirely avoided. Instead,the sensor image is separated into individual color planes (e.g., R, G,and B planes for an RGB color filter mosaic). Each color plane consistsof all the sensor pixels imaged with the corresponding color filter. Thecolor plane separation process requires far fewer machine instructionsthan the color interpolation and transformation process. The separatedcolor plane information is referred as “luminosity information”. Henceas described herein, operations on the “luminosity” image refer tooperations applied to the individual color planes in the luminosityimage. Next, the methodology of the present invention immediatelyproceeds to coding the luminosity information (i.e., the separated colorplanes). The present invention applies a wavelet transform process toprioritize information in the luminosity image (i.e., the color planesin the luminosity image are individually wavelet transformed). Thoseskilled in the art, enabled by the teachings of the present invention,will recognize that the wavelet transformation described herein couldeasily be replaced by other transform decompositions (e.g., DiscreteCosine Transform (DCT), such as used in JPEG) while still beingcompatible with the present invention.

The wavelet transform process or technique may be thought of as aprocess that applies a transform as a sequence of high- and low-passfilters. In operation, the transformation is applied by stepping throughthe individual pixels and applying the transform. This process, whichcreates an image that contains four quadrants, may for instance beperformed as follows. First, a high-pass transform then a low-passtransform is performed in the horizontal direction. This is followed bya high-pass transform then a low-pass transform performed in thevertical direction. The upper-left quadrant is derived from a low-passhorizontal/low-pass vertical image; the lower-left quadrant comprises ahigh-pass horizontal/low-pass vertical image; the upper-right quadrantcomprises a low-pass horizontal/high-pass vertical image; and thelower-right quadrant comprises a high-pass horizontal/high-pass verticalimage. The result of this is that the information most important to thehuman eye (i.e., the information, that from a luminosity or black/whiteperspective, the human eye is most sensitive to) is in the high-priority“low/low” quadrant, that is, the upper-left quadrant which contains thelow-pass horizontal/low-pass vertical image. Most of the information inthe other three quadrants, particularly the lower-right quadrant, isfundamentally zero (when based as an onset of a center frequency), thatis, image information that is least perceived by the human eye. Thus,the low/low quadrant is considered the highest-priority quadrant, withthe remaining quadrants being considered to be of much lower priority.

In basic operation, the transform process consists of processing theimage as a whole in a stepwise, linear fashion. For instance, whenprocessing the image in a horizontal direction, one would take ahorizontal vector of image data (e.g., seven horizontal neighboringpixels) and multiply that by a predetermined set of coefficients (e.g.,seven coefficients for a seven-pixel vector). This yields a single pixelvalue. Then the process continues in a sliding-window fashion byshifting over by some number of pixel(s) (e.g., two pixels), forprocessing the next vector of seven horizontal neighboring pixels. Thetransform process may be repeated multiple times, if desired. Whenrepeated, the process of applying high- and low-pass filters is repeatedfor the low/low quadrant of the then-current image (i.e., the priorresult of high-pass horizontal and vertical filtering), again generatinga four-quadrant image. Those skilled in the art will recognize that thefiltering process can be applied to the other quadrants (e.g., low/high,and the like) as well. Further, the filtering operations can becontinued recursively, further decomposing each quadrant into foursub-quadrants and so forth and so on. These quadrants are also referredto as “bands”, in the image processing literature. Whether the image istransformed with a single pass or multiple passes, the end result isstill a wavelet transformed image, which may then be readily compressed(e.g., using quantization, followed by entropy coding schemes likerun-length encoding and Huffman coding).

After generating the wavelet transformed image, the preferredmethodology of the present invention proceeds to apply quantization tothe image. This process involves dividing the wavelet transformed databy a number (called the “quantization step size”) to reduce the bitdepth of the wavelet data. The step size can be changed for each band ofthe wavelet data. Typically higher frequency bands are divided by largernumbers to de-emphasize the bands. Correspondingly, the wavelet data is“dequantized,” i.e., multiplied by the quantization step size duringdecompression (at the server/desktop). The process of quantization anddequantization involves loss of precision, and is typically the onlylossy stage during compression. At this point, the image information(i.e., all quadrants and subquadrants) can be compressed as if it werefundamentally just a normal binary file. Thus, one can apply a simple,conventional compression as a compute-efficient compression process. Ina preferred embodiment, the compression process is actually performed intwo stages. In a first stage, run-length encoding (RLE) is applied tocompress the image data. The insignificant regions of the image data(i.e., the regions that intersect high pass filters) tend to bepredominantly centered around a single value; these can be compressedsubstantially. When applying run-length encoding to this type ofinformation, for instance, one gets extremely long runs of similar data.Thus, in a preferred embodiment, the image data is compressed in a firststage using run-length encoding. This target result may then, in turn,be further compressed using Huffman coding, for generating a finalcompressed luminosity record that is suitable for storage on a digitalcamera and for wireless transmission.

Thus as described above, the camera-implemented portion of imageprocessing foregoes color processing. Instead of performingcompute-intensive tasks, such as color interpolations and YUVtransformations, the methodology performs trivial color planeseparation. This is followed by wavelet decomposition, quantization, andgeneric binary compression (e.g., run-length and Huffman encoding).

The end result is that the amount of processing necessary to go from acaptured image to a compressed record of the captured image (i.e., arecord suitable for storage on the digital camera) is substantially lessthan that necessary for transforming the captured image into color andthen compressing it into a color-rendered compressed image. Further, theresulting compressed luminosity record, because of its increasedcompression ratios (e.g., relative to conventional JPEG), facilitateswireless (or other limited bandwidth) transfer of images to targetplatforms.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram illustrating a digital camera device suitablefor implementing the present invention.

FIG. 1B is a block diagram illustrating a digital computer suitable forimplementing distributed processing portions of the present invention.

FIG. 2 is a block diagram of a software system suitable for controllingthe computer of FIG. 1B.

FIG. 3A is a block diagram illustrating a methodology of the presentinvention for distributed digital image processing (includingcontrasting it with conventional digital image processing).

FIG. 3B is a block diagram illustrating a multi-pass wavelet transformprocess.

FIGS. 3C-I are black & white photographic images that compare theresults of JPEG compression with wavelet transform.

FIG. 4A is a block diagram illustrating overall processing at a targetplatform (e.g., server or desktop computer).

FIG. 4B is a block diagram illustrating method steps of the presentinvention for completing image processing at a target platform (e.g.,server or desktop computer).

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

The following description focuses on an embodiment of the presentinvention in a digital camera device, which is the currently-preferredembodiment. However, those skilled in the art will appreciate that thepresent invention may be embodied in other imagecapturing/recording/processing devices, including, for instance, videophones, closed-circuit cameras, video camcorders, or other devicescapable of capturing, recording, and/or processing images. Further, thedescription will focus on implementation of portions of the invention inan Internet-connected environment including a desktop and servercomputers, such as an IBM-compatible computer running under Microsoft®Windows 2000. The present invention, however, is not limited to anyparticular one application or any particular environment. Instead, thoseskilled in the art will find that the system and methods of the presentinvention may be advantageously embodied on a variety of differentplatforms, including Macintosh, Linux, BeOS, Solaris, UNIX, NextStep,and the like. Therefore, the description of the exemplary embodimentswhich follows is for purposes of illustration and not limitation.

Basic System

A. Digital Camera Hardware

FIG. 1A is a block diagram illustrating a basic image capturing andrecording system 100 suitable for implementing the present invention.For purposes of illustration, the following will focus on implementationof system 100 as a digital camera. However, as noted above, for purposesof implementing the methodology of the present invention, the system 100may also be implemented in a variety of other digital image devices.

As shown in FIG. 1A, the system 100 includes a Sensor 101, a ShutterActuator 103, an Image Processor 102, an Image (DRAM) Memory 104, a(Central) Processor 106, a Keypad and Controls 108, a Program Code FlashMemory 107, a (System) Memory 105, a Direct View Display or Viewfinder109, a Hot Shoe Interface 110, and a “Digital Film” Flash Memory 111. Asillustrated, these various components communicate with one another usinga bus architecture including, for instance, an Address Bus, a Data Bus,and an I/O (Input/Output) Bus.

The system 100 employs the Sensor 101 for basic image capture. TheSensor 101 operates, in essence, by capturing light and transformingthat into electrical voltage levels. A suitable sensor is available froma variety of vendors, including VLSI Vision, Motorola, and Toshiba. In apreferred embodiment, the Sensor 101 includes, for example, a 1280 by1024 color CMOS sensor, such as a VLSI Vision VVL 6801 CMOS sensor.However, other sensor technology is suitable, including CCD sensors.

The Sensor 101 must, of course, be part of a larger assembly to operate.Specifically, the Sensor 101 operates in conjunction with a lensassembly (not shown), or other optics to focus an image onto the sensor.The optics themselves are controllable, for instance, using aconventional aperture, focus, and shutter control mechanisms. Thecurrently-preferred embodiment uses an 18 mm fixed-focal length,fixed-aperture lens assembly to provide a broad depth of field. The lensassembly employs two manual slide controls, a macro lens control, and anexposure control. The macro control switches from normal to close modeby sliding a macro lens in and out of the lens assembly to providenormal or extreme close-up capability. The exposure control switchesfrom normal to bright light by sliding a neutral gray filter in and outof the lens assembly. Aside from choosing normal or bright light, normalor close-up mode, the camera requires no manual focusing, shutter speedor aperture adjustment. Operation is as simple as point and shoot. TheSensor 101, on the other hand, operates under control of the ImageProcessor 102, which will now be described.

The Image Processor 102, which basically operates as a state machine,provides overall control for the Sensor 101. In operation, the ImageProcessor 102 controls the Sensor 101 by, in effect, telling it what todo and when. For instance, the Image Processor 102 issues timing signalsto the Sensor 101 for indicating how the Sensor 101 should record andstream out image data. Further, the Image Processor 102 provides generalInput/Output (I/O) control that allows one to coordinate control of thesensor with other electromechanical peripherals, such as a shutter, lensaperture, or the like.

Actual implementation of the Image Processor 102 itself may beaccomplished in a variety of different ways. For a microprocessor-basedimplementation, for instance, the Image Processor 102 may be implementedas a microprocessor (e.g., PowerPC 823 microprocessor, available fromMotorola, Inc. of Schaumburg, Ill.) with DSP (digital signal processing)logic blocks, memory control logic blocks, video control logic blocks,and interface logic. Alternatively, the Image Processor 102 may beimplemented as a “camera on a chip(set)” using, for instance, a SierraImaging Raptor I or II chipset (available from Sierra Imaging, Inc. ofScotts Valley, Calif.), a Sound Vision Clarity 1 or 2 chipset (availablefrom Sound Vision, Inc. of Framingham, Mass.) or similar chipset thatintegrates a processing core with image processing periphery. In apreferred embodiment, the Image Processor 102 preferably supportshardware implementation of a wavelet transform engine complete with awavelet transform filter bank, so that the wavelet transform process maybe pipelined through a series of dedicated hardware gates (instead ofexecuted as a sequence of software instructions repeatedly loaded andprocessed by a general-purpose microprocessor).

The Image Processor 102 is not a stand-alone part but, instead, relieson the (Central) Processor 106 for control instructions. The ImageProcessor 102 sits on the Address and Data Buses and is accessible bythe Processor 106 through a series of registers. In this manner, theProcessor 106 may instruct the Image Processor 102 what to perform andwhen. For instance, the Processor 106 may instruct the Image Processor102 to turn on the Sensor 101, to capture an image at the Sensor 101,and to execute the wavelet transform. Therefore, the Image Processor 102is very much a facilitator but is not in and of itself a controller forthe system.

The Shutter Actuator 103 is a simple, generic component for controllinglight exposure on the Sensor 101. Depending on the behavior of theactual sensor employed, the Shutter Actuator 103 may not even benecessary. In particular, the Shutter Actuator 103 is employed in thoseinstances where the Sensor 101 requires a black reference. In such anembodiment, the Shutter Actuator 103 is an electromechanical interfacecoupled to a solenoid which, when the interface responds to a particularlogic level, triggers an open/close cycle of a mechanical shutter. Themechanical shutter, which serves to selectively block light entering thelens assembly of the camera, may be of a conventional design availablefrom a variety of suppliers. A suitable supplier includes, for instance,Sunex, Inc. of Carlsbad, Calif.

The Image Memory (DRAM) 104 serves to store the image captured from thesensor. The Sensor 101 itself does not “store” the image that itcaptures. Therefore, the Image Memory 104 is an image capture andin-place transform (frame) buffer. This memory is controlled by theImage Processor 102 and can be shut off when not in use for power savingpurposes. During basic operation of the camera, the captured image istransferred directly into the Image Memory 104, using a sample/transfertechnique. In order to make this efficient, the process is controlled bythe Image Processor 102 in a manner somewhat akin to DMA (direct memoryaccess) transfer employed on desktop computers. Here, the ImageProcessor 102 functions as a state machine which simply samples andtransfers information from the Sensor 101 to the Image Memory 104. Inthe presently-preferred embodiment, the Image Memory 104 comprisesconventional DRAM (dynamic random-access memory) memory available from avariety of vendors, including, for instance, Toshiba, Micron, Hitachi,Samsung, and others. A size of about 4 MB (megabyte) or more is suitablefor this component.

The next several components discussed, which may be viewed as componentshanging off of the Address and Data Buses of the Processor 106, aretypical components that one would ordinarily expect to find whenimplementing a data processing device; collectively, these componentsmay be viewed as a computer embedded in the camera. For example, thesecomponents include the previously-mentioned general-purposemicroprocessor (Processor 106) coupled to memory (System Memory 105 andProgram Code Flash Memory 107). The Working or System Memory 105 is thegeneral working or scratchpad memory for the Processor 106. This memoryis used for storing program-created variables, stacks, heap(s), and thelike. In the presently-preferred embodiment, the System Memory 105comprises static RAM (e.g., SRAM), which is also available from avariety of vendors. A size of about 128 KB (kilobyte) or more issuitable for this purpose. The Program Code Flash Memory 107, on theother hand, comprises 1 MB of directly addressable flash storage thatholds the operating system and embedded software, that is, the programcode comprising the instructions that the processor must execute tooperate. The flash memory, which may be conventional flash memory thatis available from a variety of vendors, need not be of the removabletype, as the Program Code Flash Memory 107 is not intended to be removedfrom the system by the camera user.

The Processor 106 itself, in the presently-preferred embodiment,comprises a 32-bit RISC ARM Processor designed by ARM Limited ofMaidenhead, UK. ARM licenses its designs to semiconductor partners formanufacture, supply. and support; for a list of ARM licensees, see e.g.,http://www.arm.com/Partners/. The ARM processor has an efficientinstruction set that is ideal for performing cyclical functions quiterapidly and includes sufficient bandwidth for transferring large amountsof data quickly (e.g., for performing Huffman coding on a large amountof data). Additionally, the processor is a dedicated processor, withoutthe overhead of a substantial number of peripherals. These features makethe processor attractive for use in a digital camera embodiment.

For a camera embodiment, the device will, in general, be expected toinclude an interface that is capable of receiving input from users.Keypad and Controls 108 are conventional inputs that support user input.Similarly, the Direct View Display (“Viewfinder”) 109 is a direct viewLCD (liquid crystal display) that provides feedback to the user orcamera operator. During photography mode, the Viewfinder 109 replacesthe plastic viewfinders and LCD panels found on most digital cameras andprovides the most accurate real-time representation of the scenevisualized by the sensor. The Viewfinder 109 overlays simple icons ontothe image to indicate the status of various camera settings. TheViewfinder 109 fits inside an eyepiece which keeps sunlight out andallows the operator to visualize the scene in any lighting conditions.During preview mode, the Viewfinder 109 shows previews of the capturedphotos and allows the operator to delete unwanted photos or tag photosfor wireless transmission. Thus for a camera embodiment, the Viewfinder109 is used to provide a representation of the image that is beingcaptured, in preview and/or post-capture fashion.

In order to provide the display image to the Viewfinder 109, the Sensor101 is sub-sampled at a rate to create a version of the imageappropriate for display. During preview processing, the systemcontinuously captures the sensor mosaic and sub-samples the resultingmosaic for preview purposes. A histogram of the sampled luminosity isfed into a “linearization” filter to produce a balanced dynamic rangefor best optical perception. The scaled and “linearized” image is thendisplayed on the viewfinder module. The histogram data is then adjustedto match the preview image for use in linearizing the next image. Thecycle is repeated continuously to provide a real time viewfindermechanism. The Viewfinder 109 itself typically operates in conjunctionwith a display controller and a frame buffer (not shown), both of whichmay be integrated within the display component itself.

Both the Keypad and Controls and Display components, which may beconventional in nature, interface directly with the Processor 106through general I/O (e.g., I/O Bus). Typically, such devices communicatewith the microprocessor through means of interrupt requests (IRQ). Boththe Keypad and Controls and Display components are available from avariety of vendors. Examples include Sharp, Toshiba, and Citizen ofJapan, Samsung of South Korea, and Hewlett-Packard of Palo Alto, Calif.More customized displays are available from Displaytech, Inc. ofLongmont, Colo. For an embodiment that does not need to interact withusers, such as a surveillance camera, the foregoing components may beeliminated.

Additionally for a camera embodiment, it is desirable for the device toinclude an interface for standard peripheral devices, such as adetachable flash device. This may be provided by Hot Shoe (Accessory)Interface 110, which is a general I/O port that may comprise a serialinterface of a conventional design that the camera uses to interface toits accessories via the Hot Shoe Interface. In this manner, a flashaccessory can be clipped onto the camera via the Hot Shoe Interface foradded illumination.

The Interface 110 combines a Serial Peripheral Interface (SPI) with amultiplexed I/O bus which provides a plug-and-play interface to a familyof accessories. These accessories may include, in addition to a flashunit, a wireless holster for cellular (e.g., Motorola) phones, extrafilm backs for compatibility with format digital film (e.g., Sony MemoryStick or SmartMedia), a USB cradle, an RJ-11 modem cradle, a wirelesscellular module, extender cables, and the like. In thecurrently-preferred embodiment, the interface is based on theI²C-standard serial interface, which supports logic allowing the deviceto sense I²C-compatible devices that are attached to the port. I²C,which stands for Inter IC Communication, is a serial bi-directionalcommunication protocol created by Philips Semiconductor (subsidiary ofPhilips Electronics, based in The Netherlands) and is used forcommunication between integrated circuits. Most systems have one masterand several slaves that communicate using only two wires. Every devicehas its own identification code. If that code is sent by the master onlythat device will respond with an acknowledgement. After theacknowledgement, the data to be communicated is sent or received by themaster. Further information about the I²C communication protocol isavailable from Philips Electronics of The Netherlands. As with theKeypad and Controls 108 and Direct View Display or Viewfinder 109, theHot Shoe Interface 110 itself is not required for implementing the imagecapturing and processing methodology of the present invention. In thespecific embodiment of a consumer product such as a camera, though,these components typically would be included.

The system includes Digital Film Flash Memory 111, which serves as the“digital film” for the system for storing compressed images. The FlashMemory 111 may comprise available flash memory removable media, such asCompactFlash, DataFlash, and Sony Memory Stick, typically in a 16 MB orlarger size. Available vendors for flash memory include, for example,SanDisk of Sunnyvale, Calif. or Sony of Japan. Alternatively, the FlashMemory 111 may be affixed directly (i.e., non-removable) to the system100. In such an embodiment, the additional bulk associated with aremovable media cartridge holder and its accompanying interface may beavoided. Those skilled in the art will appreciate that the system 100may incorporate other non-volatile memory configurations and designsthat readily accommodate the image capture and processing methodology ofthe present invention. In general, for a consumer device embodiment, oneshould choose media that accommodates on the order of 100 compressedimages or more.

The camera embodiment is powered by a single CR-123 lithium battery (notshown), provided with instant-on capability. Due in part to thedistributed image processing approach of the present invention (presentbelow), the camera has significant power savings over other cameradesigns. This gives the device not only a size and weight advantage overother cameras but also a battery life advantage.

For connectivity, the system includes a wireless holster, a USB cradle,and a modem cradle. The wireless holster physically connects the camerato a cellular phone (e.g., Motorola cellular phone) and interfaces theHot Shoe Interface to the phone's external accessory plug. The cameracan be easily pulled out of the holster for use and clipped back in fortransmission. Detection of the holster and phone signal is automatic toallow for hands free transmission and there is no risk of corruption dueto interruption by either loss of signal or unclipping. The camera clipsinto the USB cradle through the Accessory Hot-Shoe to provide rapidphoto interchange to a personal computer equipped with a standard USBport. The USB cradle acts a USB slave device and therefore requires nobatteries or power supply for operation and instead draws its power fromthe PC. The camera can also clip into a modem cradle through the HotShoe Interface. The modem cradle allows the camera to transmit images tothe PhotoServer via a land line connection (e.g., 33.6 KBps) via astandard RJ-11 phone jack. The modem cradle is powered by the battery inthe camera.

The specifications for the currently-preferred camera embodiment may besummarized as follows.

TABLE 1 Miniature Wireless Digital Camera specifications: Sensor: 1.3Mega-Pixel Color CMOS Optics: 18 mm Fixed Focal Length, Fixed ApertureExposure Control: Automatic, Macro Mode, Indoor/Outdoor Mode Processor:ARM 32-bit RISC Chipset: Image Processor (Lightsurf PhotonOne) Memory: 4Mbytes DRAM + 128 Kbytes SRAM Digital Film: 16 Mbytes Internal FlashFilm File Format: Progressive Photograph Format (PPF) Wireless Protocol:communication protocol, such as packet-based TCP/IP, WAP, or the likeBattery: CR-123 Accessory Interface: Accessory Hot-Shoe Accessores:Flash Unit, Extra Film Back, Motorola Cellular Holster, USB Cradle,Modem Cradle

B. Basic Computer Hardware (e.g., for Desktop and Server Computers)

Portions of the present invention may be implemented on a conventionalor general-purpose computer system, such as an IBM-compatible personalcomputer (PC) or server computer. FIG. 1B is a very general blockdiagram of an IBM-compatible system 100, which is adapted to includeportions of the distributed image processing of the present invention.As shown, system 150 comprises a central processor unit(s) (CPU) 151coupled to a random-access memory (RAM) 152, a read-only memory (ROM)153, a keyboard 156, a pointing device 158, a display or video adaptor154 connected to a display device 155, a removable (mass) storage device165 (e.g., floppy disk), a fixed (mass) storage device 166 (e.g., harddisk), a communication port(s) or interface(s) 160, a modem 162, and anetwork interface card (NIC) or controller 161 (e.g., Ethernet).Although not shown separately, a real-time system clock is included withthe system 150, in a conventional manner.

CPU 151 comprises a processor of the Intel Pentium® family ofmicroprocessors. However, any other suitable microprocessor ormicrocomputer may be utilized for implementing the present invention.The CPU 151 communicates with other components of the system via abi-directional system bus (including any necessary I/O controllercircuitry and other “glue” logic). The bus, which includes address linesfor addressing system memory, provides data transfer between and amongthe various components. Description of Pentium-class microprocessors andtheir instruction set, bus architecture, and control lines is availablefrom Intel Corporation of Santa Clara, Calif. Random-access memory 152serves as the working memory for the CPU 151. In a typicalconfiguration, RAM of sixteen megabytes or more is employed. More orless memory may be used without departing from the scope of the presentinvention. The read-only memory (ROM) 153 contains the basic inputoutput system code (BIOS)—a set of low-level routines in the ROM thatapplication programs and the operating systems can use to interact withthe hardware, including reading characters from the keyboard, outputtingcharacters to printers, and so forth.

Mass storage devices 165, 166 provide persistent storage on fixed andremovable media, such as magnetic, optical or magnetic-optical storagesystems, or flash memory, or any other available mass storagetechnology. The mass storage may be shared on a network, or it may be adedicated mass storage. As shown in FIG. 1B, fixed storage 166 stores abody of program and data for directing operation of the computer system,including an operating system, user application programs, driver andother support files, as well as other data files of all sorts.Typically, the fixed storage 166 serves as the main hard disk for thesystem and stores application software implementing the PhotoServer(PhotoDesktop) component described below.

In basic operation, program logic (including that which implementsmethodology of the present invention described below) is loaded from thestorage device or mass storage 166 into the main (RAM) memory 152, forexecution by the CPU 151. During operation of the program logic, thesystem 150 accepts user input from a keyboard 156 and pointing device158, as well as speech-based input from a voice recognition system (notshown). The keyboard 156 permits selection of application programs,entry of keyboard-based input or data, and selection and manipulation ofindividual data objects displayed on the display screen 155. Likewise,the pointing device 158, such as a mouse, track ball, pen device, or thelike, permits selection and manipulation of objects on the displayscreen. In this manner, these input devices support manual user inputfor any process running on the system.

The computer system displays text and/or graphic images and other dataon the display device 155. Display device 155 is driven by the videoadapter 154, which is interposed between the display 155 and the system.The video adapter 154, which includes video memory accessible to theCPU, provides circuitry that converts pixel data stored in the videomemory to a raster signal suitable for use by a cathode ray tube (CRT)raster or liquid crystal display (LCD) monitor. A hard copy of thedisplayed information, or other information within the system 150, maybe obtained from the printer 157, or other output device. Printer 157may include, for instance, an HP LaserJet® printer (available fromHewlett-Packard of Palo Alto, Calif.), for creating hard copy images ofoutput of the system.

The system itself communicates with other devices (e.g., othercomputers) via the network interface card (NIC) 161 connected to anetwork (e.g., Ethernet network), and/or modem 162 (e.g., 56K baud,ISDN, DSL, or cable modem), examples of which are available from 3Com ofSanta Clara, Calif. The system 150 may also communicate with localoccasionally-connected devices (e.g., serial cable-linked devices) viathe communication (“comm”) interface 160, which may include a RS-232serial port, a Universal Serial Bus (USB) interface, or the like.Devices that will be commonly connected locally to the interface 160include laptop computers, handheld organizers, digital cameras, and thelike.

IBM-compatible personal computers and server computers are availablefrom a variety of vendors. Representative vendors include Dell Computersof Round Rock, Tex., Compaq Computers of Houston, Tex., and IBM ofArmonk, N.Y. Other suitable computers include Apple-compatible computers(e.g., Mackintosh), which are available from Apple Computer ofCupertino, Calif., and Sun Solaris workstations, which are availablefrom Sun Microsystems of Mountain View, Calif.

The above-described system 150 is presented for purposes of illustratingthe basic hardware underlying desktop and server computer componentsthat may be employed in the system of the present invention. Forpurposes of discussion, the following description will present examplesin which it will be assumed that there exists a “server” or remotedevice having information of interest to the ultimate end-user. Thepresent invention, however, is not limited to any particular environmentor device configuration. In particular, a server distinction is neithernecessary to the invention, but is used to provide a framework fordiscussion. Instead, the present invention may be implemented in anytype of computer system or processing environment capable of supportingthe methodologies of the present invention presented in detail below.

C. Basic System Software

Illustrated in FIG. 2, a computer software system 200 is provided fordirecting the operation of the computer system 150. Software system 200,which is stored in system memory 152 and on fixed storage (e.g., harddisk) 166, includes a kernel or operating system (OS) 210. The OS 210manages low-level aspects of computer operation, including managingexecution of processes, memory allocation, file input and output (I/O),and device I/O. One or more application programs, such as clientapplication software or “programs” 201 (e.g., 201 a, 201 b, 201 c),including image processing software, may be “loaded” (i.e., transferredfrom fixed storage 166 into memory 152) for execution by the system 150.

System 200 includes a graphical user interface (GUI) 215, for receivinguser commands and data in a graphical (e.g., “point-and-click”) fashion.These inputs, in turn, may be acted upon by the system 150 in accordancewith instructions from operating system 210, and/or client applicationmodule(s) 201. The GUI 215 also serves to display the results ofoperation from the OS 210 and application(s) 201, whereupon the user maysupply additional inputs or terminate the session. Typically, the OS 210operates in conjunction with device drivers 220 (e.g., “Winsock” driver)and the system BIOS microcode 230 (i.e., ROM-based microcode),particularly when interfacing with peripheral devices. OS 210 can beprovided by a conventional operating system, such as Microsoft® Windows9x, by Microsoft® Windows NT, or by Microsoft® Windows 2000, allavailable from Microsoft Corporation of Redmond, Wash. Alternatively, OS210 can also be an alternative operating system, such as IBM OS/2(available from IBM of Armonk, N.Y.) or Macintosh OS (available fromApple Computers of Cupertino, Calif.).

Distributed Digital Image Processing

A. Basic Design Consideration

The basic approach adopted by the present invention is to adopttechniques for reducing the amount of processing power required by agiven digital camera device and for reducing the bandwidth required fortransmitting image information to a target platform. Every digitalimaging device is inherently connected. Consider, for instance, adigital camera. It does not necessarily appear to be a “connected”device, as it may initially give the appearance of an end-to-endsolution, where one is capturing an image, processing that image, andthen storing it on digital film. In reality, however, the true endproduct is some type of output, such as a printed image used in adocument. As it turns out, somewhere along the way the image is takenoff the device and transmitted to yet another computing device, such asa server or desktop computer, where, for instance, the image may becropped, touched up, or otherwise processed. Therefore, a digitalimage—due to the fact that it is digital, is inherently related to allother types of computing devices that can handle images. Given thatenvironment in which digital cameras exist, there is an opportunity totake advantage of other processing power that is eventually going tocome into contact with the images that are produced by the digitalimaging device (“imager”). More particularly, there is an opportunity todefer and/or distribute the processing between the digital imager itselfand the target platform that the digital imager will ultimately beconnected to, either directly or indirectly. Therefore, rather thanattempting to invent a revolutionary way to get better hardwareperformance (i.e., better silicon technology) or a revolutionarycompression technique, the approach of the present invention is todecrease the actual computation that occurs at the digital imager:perform a partial computation at the digital imager device and completethe computation somewhere else—somewhere where time and size are not anissue (relative to the imager). In other words, recognizing that theimages captured by a digital camera will typically end up on anothercomputing device, the approach of the present invention is to takeadvantage of that fact by “re-architecting” the digital camera to deferresource-intensive computations, thereby substantially eliminating theprocessor requirements and concomitant battery requirements for digitalcameras. Further, the present invention adopts an image strategy whichfacilitates transmission of images, thereby facilitating the wirelesstransmission of digital camera images.

For purposes of determining how to defer and/or distribute processing,the overall process of digital imaging, from capturing a light image tostoring a digital representation of that image, may itself be viewed ascomprising various subprocesses. Once individual subprocesses areidentified, one can investigate various approaches for deferring and/ordistributing those subprocesses to other devices. Consider, forinstance, a decision to defer image compression. Such an approachentails immediate problems, however. The digital camera must havesufficient resources to store, at least temporarily, uncompressedimages, which tend to be quite large in size. Although storagetechnology (e.g., flash memory) can be expected to have ever-increasingcapacity, present-day storage technology makes that approachunattractive, if not impractical. Another difficulty posed by thatapproach is that the digital camera must exchange images in anuncompressed format with the target device (e.g., desktop computer).Again, such an approach is unattractive since it would require the userto spend an inordinate amount of time transferring images to the targetdevice, given the limited bandwidth that is commercially feasible fordownloading pictures from a digital camera. Therefore, an approach ofeliminating compression is not attractive, unless one can somehow obtainmassive storage and bandwidth capacity for the digital camera. Theimmediate challenge posed by a deferred/distributed processing approach,therefore, is how one can accomplish the approach in a manner that doesnot contradict the ultimate goal of obtaining quality digital images ona portable digital camera. To address this challenge, the entire imagingprocess, including its individual elements, is examined in order tofigure out how the process can be reproduced in a manner thatcompute-intensive portions of the process are performed somewhere otherthan the digital camera itself, but done so in a manner that does notcompromise the image information necessary for reconstructing a digitalimage of acceptable quality.

B. Distributed Image Processing

As illustrated in FIG. 1B, the imaging process approach of the presentinvention includes a rapid foreground process to capture and compressthe image (e.g., one second cycle) and a slower background process tofurther compress and transmit the image. The foreground process isoptimized for speed to facilitate continuous rapid snapshots while thebackground process is optimized for power. As shown, the two-stageprocessing mechanism is assisted by an imaging processing server, the“PhotoServer,” which typically includes Internet connectivity.

The first stage, the foreground stage, is performed in the cameraitself. This stage produces a highly-compressed image based on wavelettransform technology. This image is stored on the 16 MB of digital filminside the camera. The image is then transmitted to the PhotoServer(target platform) via a packet-based protocol as a ProgressivePhotograph Format (PPF) file. Suitable protocols include, for instance,Transmission Control Protocol/Internet Protocol (TCP/IP) and WirelessApplication Protocol (WAP). For a description of TCP/IP, see e.g.,Parker, T. et al., TCP/IP Unleashed, Sams Publishing, p. 33 et. seq.,the disclosure of the reference in its entirety being herebyincorporated by reference. For a description of WAP, see e.g., Mann, S.,The Wireless Application Protocol, Dr. Dobb's Journal, pp. 56-66,October 1999, the disclosure of which is hereby incorporated byreference.

The PPF mechanism allows selective transmission of varying degrees ofphotographic significance while maintaining the remaining elements ofsignificance on the digital film in the camera. A lower quality imagetransmitted to the server can later be upgraded to a higher qualityversion simply by synchronizing the remaining elements of significancestored in the PPF file. The second stage of the process, the backgroundstage, is performed on the PhotoServer. This stage completes the imageprocessing cycle and produces a high quality, color-balanced, compressedimage in a standard file format such as JPEG. A similar second stageprocess also exists in a desktop implementation, the PhotoDesktop, forcustomers who wish to transfer images to a desktop computer (as thetarget platform) using a USB (universal serial bus) cradle accessory orother communication link.

Detailed construction and operation of the foregoing is perhaps bestdescribed by way of comparison with conventional digital imageprocessing. FIG. 3A illustrates on its left-hand side a high-levelprocess or methodology 310 that comprises the individual processes(i.e., subprocesses) or steps routinely employed for digital imageprocessing. The digital imaging process or sequence 310 begins withimage capture, as represented by capture block or capture process 311.This is the process of capturing light data (image) from a sensor and,in response, generating digital representations of that data (i.e.,digital light levels based on the captured image). This is, in effect,an in-memory image of the light which has entered the camera's lens andstruck the camera's CCD or CMOS sensor. It is interesting to note thatat this point the digital camera has only captured light levels. Colorinformation per se does not yet exist. Instead, color information, whichmust be inferred, is not determined yet at this point in the digitalimaging process.

The capture process 311 is conventionally followed by a colorinterpolation (transformation) process 313, where color information mayindeed be determined and applied to the image. In practice, the camerais able to infer color information based on captured luminance data andinformation that it knows about the individual pixels and where they liewithin a matrix of color (pixels) that cover the surface of the camera'ssensor. This information is now applied to the image by the colorinterpolation process 313, which is a compute-intensive process.

Because the human eye is more perceptive to certain colors than others,further processing of the image is required. The standard color spacethat the device “sees” the image in (e.g., RGB color space or model) isnot necessarily the way that the human eye would view the image. Forinstance, the human eye has a certain distribution of retinal cones thatare more sensitive to certain wavelengths of light. Therefore, in aneffort to better match that expected by the human eye, YUVtransformation process 315 maps or translates the image (e.g., RGB-basedimage) into YUV color space, a color model which takes into accountluminance and chrominance. In YUV, Y is the luminance component, and Uand V are the color or chrominance components. Luminance serves as aquantitative measure of brightness. Chrominance, on the other hand,reflects the difference in color quality between a color and a referencecolor that has an equal brightness and a specified chromaticity. Inessence, the YUV transformation process 315 is a matrix transformation.Here, the red, green, and blue (RGB) values that apply to a particularpiece of pixel data are multiplied by a vector which, in turn,translates the values into YUV color space. Although the individualtransformation itself is not particularly complicated, the YUVtransformation process 315 is applied to every pixel of the image and,thus, consumes a lot of processing cycles. Accordingly, the YUVtransformation process 315 itself is also compute intensive.

Now, the image may be compressed as represented by compression process317. The basic approach applied in image compression is to prioritize bythe image data according to how a human eye would normally see it. Inlossy image compression technique (e.g., JPEG), the chrominance levelsthat are less important to the human eye are compressed out. Luminance,which the human eye is more sensitive to, is given priority in thecompression. Lossy techniques, which function largely by eliminatinginformation that is the least significant to the human eye, aredescribed in the technical, trade, and patent literature. See e.g.,Nelson, M. et al., The Data Compression Book, Second Edition, Chapter11: Lossy Graphics Compression (particularly at pp. 326-330), M&T Books,1996. Also see e.g., JPEG-like Image Compression (Parts 1 and 2), Dr.Dobb's Journal, July 1995 and August 1995 respectively (available on CDROM as Dr. Dobb's/CD Release 6 from Dr. Dobb's Journal of San Mateo,Calif.). The disclosures of the foregoing are hereby incorporated byreference.

After the foregoing lossy image capture process, the now-compressedimage may be stored on persistent media. As indicated by processingblock 318, conventional flash memory (or other suitable media) may beemployed for this purpose, such as any one of the flash memory varietiespreviously mentioned. The end result is a compressed JPEG file 319, asshown.

The design goal of digital cameras today is to generate at the digitalcamera itself complete color images that are compressed in a standardimage format (e.g., JPEG). This sequence, however, incurs multiplecompute-intensive processes, including the color transformation process313, the YUV transformation process 315, and the compression process317, with the end result being a relatively-large image that is notwell-suited for wireless transmission. In accordance with the teachingsof the present invention, however, the foregoing design goal is notadopted. Note that the very color images that have been processed, atgreat computational expense, into a standard image format at the digitalcamera will ultimately be transferred to another device—another piece ofcomputing hardware. If one assumes, for instance, that the images do notnecessarily have to be exactly a color JPEG (or other standard imageformat) while stored on the digital camera, but that the images will bea color JPEG ultimately (e.g., target device), then one can begin todefer some of the processes required for processing digital images. Inaccordance with the present invention, image processing of a digitalcamera is performed in such a manner so as to retain the advantage ofcompression at the digital camera but remove the compute-intensivecomponents of the process, so that they may be performed elsewhere(other than the digital camera itself). This process will now bedescribed in further detail.

The approach of the present invention exploits the fact that there isreally no such thing as “color sensitivity” on the digital camera.Instead, the camera uses a color inference transformation that employs amosaic pattern of color pixels overlaid on a light-level sensor (e.g.,CCD or CMOS sensor). For instance, as light shines through a red tile onthe mosaic, it lights up the light-sensing element behind it. Thatelement, in turn, records the luminosity observed. The digital cameramay then employ its internal knowledge of the mosaic pattern—thespecific arrangement of red, green, and blue pixels (of which there area variety of standard patterns)—to infer the actual color. Each patternitself tends to be a small, repeating pattern that is capable of beingrepresented with a small amount of data. For example, a Bayer patternwill consist of a 2×2 pixel section (four pixels total) of two greenpixels on one diagonal and a red and blue on another diagonal that isrepeated over and over again. A simplistic approach to using the lightinformation arriving at a particular pixel section is to merge together(i.e., matrix transformation) the information to produce four pixelshaving the same RGB level, at one quarter the resolution, but withaccurate color data. Another approach is to take into account theluminosity observed at each of the pixels, so that not only is colorinformation incorporated into the image processing but also thesharpness that is being perceived by each sensor as well.

The color interpolation process does not itself enhance the image data.Although it is certainly required for ultimately rendering a colorimage, it itself need not necessarily be performed at the digital cameraand can therefore be deferred. Stated differently, if the knowledge ofthe color pattern can be placed somewhere else and the color image neednot be completely generated right away (i.e., at the digital camera),then the step or process of transforming the originally-captured imageinto a color image may be deferred. In accordance with the presentinvention, the color interpolation and transformation process is in factdeferred altogether. Instead, the R, G, B color planes are separated andcompressed. The compressed images are packaged into a single stream withheader information to identify the individual bit-streams. The combinedbit-stream may then be transmitted to the target device, with a smalldescriptor of what Bayer pattern should be applied either beingtransmitted to or being assumed by the target device.

The right-hand side of FIG. 3A illustrates a preferred methodology 320for digital image processing in accordance with the present invention.At the outset, an image is captured by capture process 321, in a mannersimilar to that previously described for capture process 311. At themoment the shutter button is depressed, the sensor captures a fulldetail mosaic in two phases. The first phase is captured with themechanical shutter closed, the second with the shutter open. Both phaseshappen in rapid succession, with the first being used to normalize theblack level of the second. The mosaic is then fed into a linearizationfilter using the coefficients from the last preview frame prior toshutter click and serialized to DRAM. The image is also scaled to matchthe operator selected image capture resolution. Any aberrant pixel datashould fall outside of the dynamic range provided by the histogram andconsequently be canceled out.

Next, the color interpolation or transformation process is entirelyavoided. Instead, the methodology 320 immediately moves to extraction ofthe color planes, shown as color plan separation process 323, followedby a wavelet transform process 330 to prioritize information in thecolor planes. Here, the separated color planes are fed into a wavelettransform image—that is, a preferably hardware-implemented (forperformance) wavelet transform process. Over a series of repeatedcycles, the wavelet engine transforms the luminosity image in place inDRAM.

The wavelet transform process itself may be thought of as a process thatapplies a transform as a sequence of high- and low-pass filters. Inoperation, the transformation is applied by stepping through theindividual pixels and applying the transform. This process, whichcreates an image that contains four quadrants, may for instance beperformed as follows. First, a high-pass transform then a low-passtransform is performed in the horizontal direction. This is followed bya high-pass transform then a low-pass transform performed in thevertical direction. The upper-left quadrant is derived from a low-passhorizontal/low-pass vertical image; the lower-left quadrant comprises ahigh-pass horizontal/low-pass vertical image; the upper-right quadrantcomprises a low-pass horizontal/high-pass vertical image; and thelower-right quadrant comprises a high-pass horizontal/high-pass verticalimage. The result of this is that the information most important to thehuman eye (i.e., the information that, from a luminosity or black/whiteperspective, the human eye is most sensitive to) is in the high-priority“low/low” quadrant, that is, the upper-left quadrant which contains thelow-pass horizontal/low-pass vertical image. Most of the information inthe other three quadrants, particularly the lower-right quadrant, isfundamentally zero (when based as an onset of a center frequency), thatis, image information that is least perceived by the human eye. Thus,the low/low quadrant is considered the highest-priority quadrant, withthe remaining quadrants being considered to be of much lower priority.

The transform is a completely reversible process, such that the originalimage (luminosity record) may be restored without loss of information.In practice, however, some information is lost as a result the processbeing performed digitally, as digital computing devices are of courseonly able to perform real number math with finite, not infinite,precision. Nevertheless given enough digital significance (that istypically available with processors today), this loss is imperceptibleto the human eye. The human eye is perceptive only to a bit depth in therange of about five to six significant bits of image data (based on acertain center frequency). As a result, processing the image with evenmodest processing capability (e.g., a bit depth of 16 significant bits)generates a transform that is reversible in a manner that is notperceptible to the human eye. Here, the image data is arranged withoutany reliance on color in such a way that the information most importantto the human eye is one-quarter of its original size. If desired, thebest-perceived quadrant (e.g., the upper-left quadrant for the examplesequence above) may be used as a basis to provide the user with a blackand white image at the digital camera (e.g., for preview purposes).

In basic operation, the transform process consists of processing theimage as a whole in a stepwise, linear fashion. For instance, whenprocessing the image in a horizontal direction, one would take ahorizontal vector of image data (e.g., seven horizontal neighboringpixels) and multiply that by a predetermined set of coefficients (e.g.,seven coefficients for a seven-pixel vector). This yields a single pixelvalue. Then the process continues in a sliding-window fashion byshifting over by some number of pixel(s) (e.g., two pixels), forprocessing the next vector of seven horizontal neighboring pixels.Further description of the wavelet transform process may be found, forinstance, in the technical and trade literature. See e.g., Pigeon, S.,Image Compression with Wavelets, Dr. Dobb's Journal, August 1999, pp.111-115. The disclosure of the foregoing is hereby incorporated byreference, for all purposes.

As illustrated in FIG. 3B, the wavelet transform process may be repeatedmultiple times, if desired. When repeated, the process of applying high-and low-pass filters is repeated for the low/low quadrant of thethen-current image (i.e., the prior result of high-pass horizontal andvertical filtering), again generating a four-quadrant image. Forinstance, as shown in FIG. 3B, the wavelet transformed image 370, whichhas already undergone a first pass of the wavelet transform, issubjected to another pass of the wavelet transform process to generatewavelet transformed image 380—that is, an image that has undergone tworounds of wavelet transformation. The process may continue in thisfashion, for example, generating wavelet transformed image 390. Eachtime, the subsequent pass is performed on the prior-resulting low/lowquadrant. Those skilled in the art will recognize that other quadrantscould also be decomposed in a similar manner. This process may continuerecursively until the desired transformed image is obtained. Whether theimage is transformed with a single pass or multiple passes, the endresult is still a wavelet transformed image. This image is “quantized”(i.e., reduced in bit-depth) by dividing the wavelet coefficients (i.e.,the numerical value of the pixels in the wavelet transformed image) by aquantization scale factor. The quantization can differ from one band toanother. The quantizations step sizes will be included in compressedbit-stream and will be used by the decompression system (e.g., on thedesktop/server) to reverse the above process. Note that quantization anddequantization leads to loss of precision in the wavelet data andrepresents the lossy part of the compression. After quantization, thewavelet coefficients are compressed losslessly by one of several genericbinary compression techniques (e.g., bit-plane decomposition of bands,followed by arithmetic coding).

After generating the wavelet transformed image, therefore, the preferredmethodology 320 of the present invention proceeds to apply compressionto the image. At this point, the image information (i.e., all quadrantsand subquadrants) can be compressed as if it were fundamentally just anormal binary file. Thus, one can apply a simple, conventionalcompression, as a compute-efficient compression process, as indicated bycompression process 340. In a preferred embodiment, the compression isperformed in succession stages. First, run-length encoding (RLE) isapplied to compress the image data. RLE itself is a simple, well-knowntechnique used to compress runs of identical symbols in a data stream.The insignificant regions of the image data (i.e., the low-priorityquadrants) tend to be predominantly centered around a single value;these can be compressed substantially. When applying run-length encodingto this type of information, for instance, one gets extremely long runsof similar data. The image is serialized to flash memory during theencoding process to free the DRAM for the next image capture. The entirecycle from image capture through stage one compression and serializationto flash is rapid (e.g., less than one second) for the highest qualitymode. The camera is then ready to take another photograph. RLE, whichtypically encodes a run of symbols as a symbol and a count, is describedin the patent, technical, and trade press; see, e.g., Zigon, Robert,Run-Length Encoding, Dr. Dobb's Journal, February 1989 (available on CDROM as Dr. Dobb's/CD Release 6 from Dr. Dobb's Journal of San Mateo,Calif.), the disclosure of which is hereby incorporated by reference. Inaddition to RLE, the methodology 320 may include discarding low prioritydata in order to provide more-aggressive lossy compression.

This target result may then, in turn, be further compressed usingHuffman coding, for generating a final compressed luminosity record 350that is suitable for storage on a digital camera and for wirelesstransmission. Huffman coding is a method of encoding symbols that variesthe length of the symbol in proportion to its information content.Symbols with a low probability of appearance are encoded with a codeusing many bits, while symbols with a high probability of appearance arerepresented with a code using fewer bits. Huffman coding is described inthe patent, technical, and trade press; see, e.g., Nelson, M. et al.,The Data Compression Book, Second Edition, Chapters 4 and 5, M&T Books,1996, the disclosure of which is hereby incorporated by reference.

The wavelet transform-based compression used in the digital camera 100achieves significantly better image quality than traditional JPEGcompression used in other digital cameras. The image comparisonspresented in FIGS. 3C-I illustrate this. The standard reference imagefor compression algorithms is the Lena image, shown in FIG. 3C inoriginal uncompressed detail. The following image sets illustrate theresulting relative image degradation of wavelet and JPEG techniques forvarying compression ratios. At an ultra-aggressive 48:1 compressionratio, the Lena image is still of reasonable quality using wavelettransform (FIG. 3E) while JPEG (FIG. 3D) has generated unacceptablepixelization. At a compression ratio of 32:1, the Lena image is showingbetter edge detail with wavelet transform (FIG. 3G) while JPEG (FIG. 3F)is still largely pixelized and unacceptable. At a compression ratio of16:1, the fast quality compression ratio, wavelet transform (FIG. 31)has produced a good quality image with good edge definition and fewnoticeable artifacts. JPEG (FIG. 3H), on the other hand, is barelyapproaching an acceptable image comparable with a wavelet ratio of 32:1or more. Thus, the foregoing demonstrates that the wavelettransform-based compression technique produces far better shadecontinuity and edge detail than equivalent JPEG.

Thus as described above, the camera-implemented portion of imageprocessing (i.e., methodology 320) foregoes color processing. Instead ofperforming YUV transformation, the methodology performs wavelettransform compression on an image comprising a luminosity record.Further, JPEG-style compression, which is fairly compute-intensive, hasbeen removed. Instead, the methodology 320 applies generic binarycompression (e.g., run-length encoding and Huffman coding), which is farless compute-intensive. Note in particular that, up to this point, imagecompression in accordance with the present invention has been performedin a manner which is largely lossless, not lossy. Loss of imageinformation at this point, which is quite small, is due only to digitalrounding errors. If desired, however, additional compression techniques,including lossy ones, may be applied (e.g., at additional compressionprocess 340). For instance, the image may be further compressed byreducing the bit depth in the low priority quadrants.

The end result is that the amount of processing necessary to go from acaptured image to a compressed record of the captured image (i.e., arecord suitable for storage on the digital camera) is substantially lessthan that necessary for transforming the captured image into color andthen compressing it into a color-rendered compressed image. Further, theresulting compressed luminosity record, because of its increasedcompression ratios (e.g., relative to conventional JPEG), facilitateswireless (or other limited bandwidth) transfer of images to targetplatforms.

The compressed luminosity record 350 is of course optimized forgeneration and storage on a digital camera, not for viewing by the user.Thus at the point where the compressed luminosity record 350 istransferred to another computing device (e.g., images downloaded to adesktop computer), image processing crosses over the distributedboundary to continue image processing on the target platform. In thecurrently-preferred embodiment, this is done via wireless transmission.Whenever the camera is connected to the cellular holster via theHot-Shoe clip, a background process is initiated to transmit any pendingcompressed PPF photographs to the PhotoServer for final processing. Theprocess is transparent to the user, requiring no operator interventionand can occur while the camera is in low power mode. Using WPTP as thetransport layer, the process can be interrupted at any time withoutworry of any data corruption or need to re-send already transmittedpackets.

Estimates for wireless transmission times follow in the tables below.These estimates are shown with varying operator-selectable imageresolution and varying operator selectable image quality. Image qualityis a factor of compression ratio. As compression ratios increase, moreloss of significant image data occurs.

TABLE 2 Wireless transmission times assuming a 10 Kbps transmission rateResolution Photographic Standard Internet Quality 1280 × 1024 1024 × 768512 × 384 High (4:1) 255 seconds 153 seconds  38 seconds Standard (8:1)126 seconds 76 seconds 19 seconds Fast (16:1)  63 seconds 38 seconds  8seconds

TABLE 3 Wireless transmission times assuming a 56 Kbps transmission rateResolution Photographic Standard Internet Quality 1280 × 1024 1024 × 768512 × 384 High (4:1) 51 seconds 31 seconds 8 seconds Standard (8:1) 23seconds 15 seconds 4 seconds Fast (16:1) 13 seconds  8 seconds 2 seconds

As an option, an operator can also transmit the PPF photographs to apersonal computer via the USB cradle. This process employs the samepacket-based communication protocols except that it happens over awire-line connection and in the foreground. Photographs transmitted tothe PhotoServer or to the PhotoDesktop can be synchronized usingsections of the PPF file. Synchronization is the act of supplying anysupplemental data to images in order to enhance them to the maximumquality PPF record available. For instance, synchronization of a fastquality PPF file and a high quality PPF file of the same image willresult in enhancement of the fast quality image to high quality.

The Progressive Photograph Format (PPF) itself comprises a sequence ofsequential image sections ordered by decreasing optical significance.The first section is the most significant image data and represents acomplete fast quality version of the image. This is followed by sectionstwo and three which contain subsequent detail data to enhance the imageto normal quality and high quality respectively. Using the PPF approach,a fast quality image can be transmitted to the PhotoServer, takingmaximum advantage of transmission data size and speed. The server imagecan then be synchronized with the remaining components of the PPF fileat a later time to restore the image to its original maximum quality.With this unique approach, the operator does not have to sacrifice imagequality in order to maximize wireless throughput.

Now, the remainder of image processing can be performed at the targetplatform (e.g., server or desktop computer) in a straightforward manner,without the size and portability constraints that are imposed on thedigital camera. Moreover, one can apply all of the processor capabilityof the target platform. Note, however, that the foregoing approach maybe modified so that the image is (optionally) color processed at thedigital camera (e.g., for viewing as a color JPEG file), yet transmittedas a PPF file, thus preserving the high-compression benefit for wirelesstransmission.

FIG. 4A provides an overview of the completion of image processing atthe target platform. The PhotoServer receives highly compressed PPFfiles from the digital camera and completes the image processing cycle.In the decompression phase, a decompressed image is reconstructed fromthe PPF file. The resulting image is then run through an artifactreduction filter which compensates for artifacts introduced by thecamera during the compression process. The result is then arranged intothe original sensor color mosaic. The image is then processed by thecolor interpolation engine, which removes the mosaic pattern andproduces a high quality color image. The resulting image is in the RGBcolor space. Next the color characterization profile of the specificcamera (recorded at factory assembly time) is used to balance the colorsin the image to match human color perception. This stage makes up forthe differences in how the camera sensor and the human eye see color.The image enhancement phase is optional. In this phase the balancedcolor image is processed to reduce red-eye artifacts, to enhancecontrast, to harden and smooth edges, or even to interpolate to a higherresolution. Finally, the image is again compressed. The resulting outputis an industry standard, high quality color image file such as JPEG,JPEG 2000 or FlashPix.

FIG. 4B illustrates specific method steps involved at the targetplatform. First, the decompression process 410 decompresses thecompressed luminosity record (e.g., reversing the Huffman coding and RLEcompression). Thereafter, the wavelet transform is reversed, forrestoring the uncompressed luminosity record. This is illustrated by theinverse wavelet transform process 420. Reversing the wavelet transformprocess yields an uncompressed luminosity record 430—that is, a recordof that which was originally sent from the camera's sensor, in fullresolution. As previously noted, some loss of information from theoriginal luminosity record may result, but it is typically at a ratethat is imperceptible to the human eye. It is possible to have nearlossless compression/decompression but, in the preferred embodiment,some controlled loss is accepted in order to further optimize theprocess (e.g., avoid adding precision that would not result in betterimage quality, as perceived by the user). As indicated by process block440, conventional image processing (e.g., process steps 315-319) can nowbe applied to the uncompressed luminosity record for generating a colorimage for storage in a desired (e.g., typically standardized) fileformat. The end result is that one still ends up with a color digitalimage stored in one of the standardized formats (e.g., JPEG image 450).After processing the image, the PhotoServer may conveniently be used tofurther propagate the image, such as making the image available over theInternet to a multitude of other users (e.g., family and friends of thecamera user). The image may, of course, also be rendered in hard copy,using a printing device available to the computer.

Note that, in accordance with the teachings of the present invention,the compute-intensive elements of digital image processing have beendeferred such that they need not be performed at the digital camera but,instead, are deferred until the image arrives at the target platform(e.g., more-powerful desktop or server computer). In this manner, theamount of processing capability required at the camera is decreased, orfor a given level of processing power the images may be processed fasterat the digital camera. Additionally, the bandwidth required to transmitimages from the digital camera to the target platform is substantiallyreduced, thereby facilitating wireless transmission of the images. Atthe same time, the present invention accomplishes this without losingthe advantages of high compression, such as decreased storagerequirement and decreased transmission time for downloading images.

While the invention is described in some detail with specific referenceto a single-preferred embodiment and certain alternatives, there is nointent to limit the invention to that particular embodiment or thosespecific alternatives. Thus, the true scope of the present invention isnot limited to any one of the foregoing exemplary embodiments but isinstead defined by the appended claims.

1. In a digital imaging system, a method for distributed digital imageprocessing, the method comprising: recording luminosity information at afirst device, for representing an image that has been digitally capturedat the first device; without performing color interpolation at the firstdevice, generating compressed luminosity information at the first deviceby applying a wavelet transform compression to individual color planesthat comprise the luminosity information, followed by applyingquantization and compression to the luminosity information; packagingsaid compressed luminosity information, in a plurality of data packetssuitable for progressive transmission of image data corresponding tovarying levels of photographic significance, with header informationidentifying the individual color planes that comprise the luminosityinformation; progressively transmitting a first set of data packets fromsaid plurality of data packets of said compressed luminosity informationto a second device, while remaining data packets from said plurality ofdata packets are maintained at the first device; restoring saidluminosity information from said first set of data packets of saidcompressed luminosity information at the second device; converting saidluminosity information at the second device into a color image,including performing color interpolation at the second device,corresponding to the progressively transmitted data packets received bythe second device; and in response to receipt of a second set of datapackets from the remaining data packets, said second set of data packetscorresponding to a higher level of photographic significance, convertinga lower-quality representation of the image into a higher-qualityrepresentation by synchronizing said lower-quality representation withsaid higher-quality representation at the second device.
 2. The methodof claim 1, wherein said luminosity information comprises light-levelinformation for representing an image that has been digitally capturedat the first device.
 3. The method of claim 1, wherein said generatingstep includes: applying generic binary compression to said compressedluminosity information at the first device.
 4. The method of claim 3,wherein said step of applying generic binary compression includesapplying run-length encoding.
 5. The method of claim 3, wherein saidstep of applying generic binary compression includes applying Huffmancoding.
 6. The method of claim 1, wherein said restoring step includes:reversing said compression that occurred at the first device.
 7. Themethod of claim 1, wherein said step of converting said luminosityinformation into a color image includes: interpolating color informationfor the image from said luminosity information.
 8. The method of claim7, wherein said interpolating step includes: apply a YUV transformationto said luminosity information at the second device for converting saidluminosity information into a color image in YUV color space.
 9. Themethod of claim 7, wherein said step of converting said luminosityinformation into a color image further includes: converting the colorimage into a standard file format at the second device.
 10. The methodof claim 9, wherein said standard file format comprises a JPEG fileformat.
 11. The method of claim 9, wherein said step of converting saidluminosity information into a color image further includes: applyingJPEG compression to the color image at the second device.
 12. The methodof claim 1, wherein said step of transmitting said compressed luminosityinformation to a second device includes: transmitting said compressedluminosity information from a digital camera to a computer using apacket-based communication protocol.
 13. The method of claim 12, whereinsaid step of transmitting said compressed luminosity information from adigital camera to a computer using packet-based communication protocolincludes: selectively connecting the digital camera to a cellular phonefor establishing a wireless communication session with the computer. 14.The method of claim 1, wherein said second device comprises a computerwith connectivity to the Internet and wherein said method furtherincludes making the color image available to multiple users.
 15. In adigital imaging system, a method for deferring digital image processing,the method comprising: recording sensor information from an image sensorat a first device, for representing an image that has been recorded atthe image sensor of the first device; compressing said sensorinformation prior to color processing by applying a transformationcompression to individual color planes that comprise the sensorinformation, for generating compressed sensor information at the firstdevice; packaging said compressed sensor information, in a plurality ofdata packets suitable for progressive transmission of image datacorresponding to varying levels of photographic significance, withheader information identifying the individual color planes that comprisethe sensor information; without having performed color processing at thefirst device, progressively transmitting a first set of data packetsfrom said plurality of data packets of said compressed sensorinformation to a second device, while remaining data packets from saidplurality of data packets are maintained at the first device;decompressing said compressed sensor information at the second device,whereupon said sensor information may thereafter be processed into acolor image corresponding to the progressively transmitted data packetsreceived by the second device; and in response to receipt of a secondset of data packets from the remaining data packets, said second set ofdata packets corresponding to a higher level of photographicsignificance, decompressing said second set of data packets to convert alower-quality representation of the image into a higher-qualityrepresentation by synchronizing said lower-quality representation withsaid higher-quality representation at the second device.
 16. The methodof claim 15, wherein said sensor information comprises light-levelinformation for representing an image that has been digitally recordedat the first device.
 17. The method of claim 15, wherein saidcompression step includes: applying a wavelet transform to individualbit planes that comprise the sensor image; and applying compression tothe transformed sensor image, to create said compressed sensorinformation at the first device.
 18. The method of claim 17, whereinsaid step of applying compression to the transformed sensor imageincludes: applying compression using run-length encoding.
 19. The methodof claim 17, wherein said step of applying compression to thetransformed sensor image includes: applying compression using Huffmancoding.
 20. The method of claim 17, wherein said decompression stepincludes: reversing said wavelet transform that occurred at the firstdevice.
 21. The method of claim 15, further comprising: converting saidsensor information into a color image by interpolating color informationfor the image from said sensor information.
 22. The method of claim 21,wherein said converting step includes: apply a YUV transformation tosaid sensor information at the second device for converting said sensorinformation into a color image in YUV color space.
 23. The method ofclaim 21, wherein said converting step includes: converting the colorimage into a standard file format at the second device.
 24. The methodof claim 23, wherein said standard file format comprises a JPEG fileformat.
 25. The method of claim 23, wherein said converting stepincludes: applying JPEG compression to the color image at the seconddevice.
 26. The method of claim 15, wherein said step of transmittingsaid compressed sensor information to a second device includes:transmitting said compressed sensor information from a digital camera toa computer in a wireless manner using a communication protocol.
 27. Themethod of claim 26, wherein said step of transmitting said compressedsensor information from a digital camera to a computer includes:selectively connecting the digital camera to a cellular phone forestablishing a wireless communication session with the computer.
 28. Themethod of claim 15, wherein said second device comprises a computer withconnectivity to the Internet and wherein said method further includesmaking the color image available to multiple users.
 29. An imagingsystem providing deferred image processing, the system comprising: animager having a sensor for recording luminosity information for a visualimage captured by the imager, said luminosity information comprisingluminosity values recorded by the sensor; a compressor module forcompressing said luminosity information by applying a transformationcompression to each individual color planes that comprise the luminosityinformation, for generating compressed luminosity information at theimager without having performed color processing, wherein the compressedluminosity information is packaged into a plurality of data packetssuitable for progressive transmission of image data, corresponding tovarying levels of photographic significance, in a bit stream with headerinformation identifying the individual color planes that comprise theluminosity information; a wireless communication link for progressivelytransmitting a first set of data packets from said plurality of datapackets of said compressed luminosity information to a target device,while remaining data packets from said plurality of data packets aremaintained in a storage coupled with a first device; a decompressionmodule for decompressing said compressed luminosity information at thetarget device, whereupon said sensor information may thereafter beprocessed into a color image corresponding to the progressivelytransmitted data packets received by the target device; and in responseto receipt of a second set of data packets from the remaining datapackets, said second set of data packets corresponding to a higher levelof photographic significance, the decompression module for decompressingsaid second set of data packets to convert a lower-qualityrepresentation of the image into a higher-quality representation bysynchronizing said lower-quality representation with said higher-qualityrepresentation at the target device.
 30. The system of claim 29, whereinsaid luminosity information comprises brightness information forrepresenting an image that has been digitally captured at the imager.31. The system of claim 29, wherein said compression module includes: ageneric binary compression module for compressing said luminosityinformation at the first device.
 32. The system of claim 31, whereinsaid generic binary compression module applies run-length encoding. 33.The system of claim 31, wherein said generic binary compression moduleapplies Huffman coding.
 34. The system of claim 31, further comprising ageneric binary decompression module for reversing generic binarycompression that has been applied at the imager.
 35. The system of claim29, wherein said target device includes: an interpolation module forinterpolating color information for the image from said luminosityinformation.
 36. The system of claim 35, wherein said interpolationmodule applies a YUV transformation to said luminosity information atthe target device for converting said luminosity information into acolor image in YUV color space.
 37. The system of claim 29, wherein saidtarget device further includes: a compression module for converting thecolor image into a standard compressed file format at the target device.38. The system of claim 37, wherein said standard compressed file formatcomprises a JPEG file format.
 39. The system of claim 37, wherein saidcompression module of said target device includes a JPEG module forapplying JPEG compression to the color image at the target device. 40.The system of claim 29, wherein said imager comprises a digital camera,wherein said target device comprises a computer, and wherein saidcommunication link is coupled to a cellular phone device fortransmitting said compressed luminosity information from said digitalcamera to said computer in a wireless manner using a communicationprotocol.
 41. The system of claim 40, wherein said communication link isselectively coupled to the cellular phone for establishing a wirelesscommunication session between the digital camera and the computer. 42.The system of claim 29, wherein said target device comprises a computerwith connectivity to the Internet, which provides access to the colorimage to multiple users.
 43. The system of claim 29, wherein said imagercomprises a selected one of a digital camera, a digital camcorder, and aclosed circuit surveillance camera.
 44. The system of claim 29, whereinsaid target device comprises a desktop computer.
 45. The system of claim29, wherein said target device comprises a server computer.
 46. Thesystem of claim 29, wherein said sensor comprises a complementarymetal-oxide semiconductor (CMOS) image sensor.
 47. The system of claim29, wherein said sensor comprises a charge-coupled device (CCD) imagesensor.
 48. The system of claim 29, wherein said luminosity informationcomprises gray-scale luminosity information, prior to being processedinto a color image.
 49. The system of claim 29, wherein said compressedluminosity information comprises a wavelet transformed and compressedluminosity record of the image recorded at the sensor.
 50. In a digitalimaging system, a method for distributed digital image processing, themethod comprising: recording luminosity information at a first device,for representing an image that has been digitally captured at the firstdevice; while deferring color interpolation to a second device,generating compressed luminosity information at the first device byapplying a wavelet transform compression to individual color planes thatcomprise the luminosity information, followed by applying quantizationand compression to the luminosity information; packaging said compressedluminosity information, in a plurality of data packets suitable forprogressive transmission of image data corresponding to varying levelsof photographic significance, with header information identifying theindividual color planes; progressively transmitting a first set of datapackets from said plurality of data packets of said compressedluminosity information to the second device, while remaining datapackets from said plurality of data packets are maintained at the firstdevice; restoring said luminosity information from said first set ofdata packets of said compressed luminosity information at the seconddevice; converting said luminosity information at the second device intoa color image, including performing color interpolation at the seconddevice, corresponding to the progressively transmitted data packetsreceived by the second device; and in response to receipt of a secondset of data packets from the remaining data packets, said second set ofdata packets corresponding to a higher level of photographicsignificance, converting a lower-quality representation of the imageinto a higher-quality representation by synchronizing said lower-qualityrepresentation with said higher-quality representation at the seconddevice.